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In this paper we derive a new design of the Convex Variable Step-Size (CVSS) algorithm, based on measurements obtained with LMS algorithm. Computer simulations are provided to support the proposed approach.
The constant modulus algorithm (CMA) is arguably the most widespread iterative method for blind equalization of digital communication channels. The present contribution studies a recently proposed technique aiming at avoiding the shortcomings of conventional gradient-descent implementations. This technique is based on the computation of the step size leading to the absolute minimum of the CM criterion...
In various adaptive array applications, the directions of arrival (DOAs) of the desired user signal are sparsely separated. As such, the desired beam-pattern has a sparse structure. We propose an NLMS based adaptive algorithm which exploits this sparse DOA structure and provides significantly improved convergence and tracking capabilities.
Mouth segmentation is an important issue which applies in many multimedia applications as speech reading, face synthesis, recognition or audiovisual communication. Our goal is to have a robust and efficient detection of lips contour. In this paper, we focus on the detection of the inner mouth contour which is a difficult task due to the non-linear appearance variations. We propose a method based on...
Many multichannel algorithms for blind channel identification and deconvolution rely on the identifiability condition that the channels are coprime, i.e. they do not have common zeros. This property has not received much attention in the literature, partly due to the difficulty of factoring the high order channel polynomials that arise in room acoustics. In this paper we propose a novel method for...
An extension of Independent Component Analysis (ICA) to the situation when the mixture of signals is contaminated by multiplicative noise is proposed in this paper. The ICA methods search for the most independent output after a linear transformation of the data vector. If the ICA model is followed by these data, the result of this search is the inverse of the unknown mixture. On the other hand, if...
A class of single-input hybrid systems is considered, where the order of singularity for each continuous subsystem is infinite. It is shown that for such systems the terminal-cost optimal solution either lies on the boundary of the feasible region or on a subset of the boundary of the invariant set. The theory is illustrated on a stick-slip inertial drive and a biofermenter.
This paper presents a new approach to fuel-optimal path planning of multiple vehicles using a combination of linear and integer programming. The basic problem formulation is to have the vehicles move from an initial dynamic state to a final state without colliding with each other, while at the same time avoiding other stationary and moving obstacles. It is shown that this problem can be rewritten...
A novel hierarchical clustering method is presented in this work. It operates as a part of a split and merge segmentation scheme. The proposed technique incorporates the use of several color features to compare clusters in the RGB space and the flexibility of the fuzzy reasoning approach to accomplish satisfactory segmentation results. The boundary values of the fuzzy sets have been determined by...
Recently, several multi-parametric Nonlinear Programming approaches to explicit solution of constrained Nonlinear Model Predictive Control (NMPC) problems have been suggested. The benefits of an explicit solution, in addition to the efficient on-line computations, include also verifiability of the implementation. However, the off-line computational complexity tends to increase rapidly with the number...
This paper proposes a novel model predictive control (MPC) scheme based on multiobjective optimization. At each sampling time, the MPC control action is chosen among the set of Pareto optimal solutions based on a time-varying and state-dependent decision criterion. After recasting the optimization problem associated with the multiobjective MPC controller as a multiparametric multiobjective linear...
The use of small sensor arrays in modern signal processing systems has recently become more common due to the increase in computational processing power and interest in intelligent sensing and surveillance. However, not much information is available on the design of small sensor arrays having arbitrary geometry, that effectively can accomplish these tasks. In this paper we address the problem of designing...
In this article, a novel low-complexity block-processing sparse system estimation method, based on least squares (LS), ℓ1-norm minimization and support shrinkage, is proposed. The proposed method can be seen as a counterpart for the Least Absolute Shrinkage and Selection Operator (LASSO), in the sense that the proposed method aims to find the vector that minimizes its ℓ1-norm subject to a maximum...
In many real-life situations, we come across problems with imprecise input values. Imprecisions are dealt with by various ways. One of them is interval based approach in which we model imprecise quantities by intervals, and suppose that the quantities may vary independently and simultaneously within their intervals. In most optimization problems, they are formulated using imprecise parameters. Such...
This paper proposes a double auction mechanism for energy trade between buying and selling agents. The framework is general enough, requiring neither the agents' preferences nor the energy pricing to be fixed values across the spatially distributed agents. A microgrid controller implements a distributed algorithm to maximize individual participating agents' utilities as well as the social welfare...
Dimensionality reduction aims at providing faithful low-dimensional representations of high-dimensional data. Its general principle is to attempt to reproduce in a low-dimensional space the salient characteristics of data, such as proximities. A large variety of methods exist in the literature, ranging from principal component analysis to deep neural networks with a bottleneck layer. In this cornucopia,...
Consider a network where each agent has a private composite function (e.g. the sum of a smooth and a non-smooth function). The problem we address here is to And a minimize! of the aggregate cost (the sum of the agents functions) in a distributed manner. In this paper, we combine recent results on primal-dual optimization and coordinate descent to propose an asynchronous distributed algorithm for composite...
This paper introduces the usage of non-convex based regularizers to solve the underdetermined MEG inverse problem. The signal to be reconstructed is considered to have a structure which entails group-wise sparsity and within group sparsity among its covariates. We discuss the usage of ℓ2 norm regularization and smoothed ℓ0 (SL0) norm regularization to impose group-wise and within group sparsity respectively...
Multi-document summary plays an increasingly important role with the exponential document growth on the web. Among many traditional multi-document summarization techniques, the latent semantic analysis (LSA) is a unique duo to its using latent semantic information instead of original feature, which results in a better performance. However, since those approaches based on LSA evaluate and select sentence...
One of the most fundamental issues in network virtualization is the virtualization of the substrate nodes. Reconfigurable Router (RR) realizes a flexible router architecture based on the idea of hardware virtualization which is performed by component-based processing and reconfiguration. But if the components are incompatible with each other in terms of performance, the RR will get lower performance...
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